Centralized Omics REsource (CORE)

集中组学资源 (CORE)

• 批准号: 9365870
• 金额: $ 0.1万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-26 至 2017-10-25
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9365870
• 关键词: Award; Behavioral; Blood; Clinical; Clinical Data; Collection; Communities; Contracts; Coupling; DNA Methylation; Data; Disease; Ensure; Genetic Transcription; Health; Heart; Image; Institutes; Lung; Medicine; Methylation; Molecular; Molecular Profiling; National Heart, Lung, and Blood Institute; Outcome; Population Heterogeneity; Precision Medicine Initiative; Proteomics; Research; Resources; Sleep Disorders; System; Trans-Omics for Precision Medicine; epigenomics; genome sequencing; genome-wide; metabolomics; precision medicine; programs; repository; whole genome

The NHLBI Trans-Omics for Precision Medicine (TOPMed) program will support the Institute’s larger precision medicine initiative by collecting and coupling whole-genome sequencing (WGS) and other -omics data (e.g., DNA methylation signature, RNA expression profiles, metabolite profiles) with molecular, behavioral, imaging, environmental, and clinical data from studies focused on heart, lung, blood and sleep (HLBS) disorders. The TOPMed program aims to: •Collect and assemble -omics (RNASeq, methylation, metabolomics, epigenomics, and proteomics) data with WGS and clinical outcomes data across diverse populations including those traditionally underrepresented in research. •Build a data commons repository that the scientific community can use for future research and to enable precision medicine. •Stimulate systems medicine approaches that help organize data to ensure they are accessible and interpretable for health disease research. •Promote discoveries about the fundamental mechanisms that underlie HLBS disorders.

NHLBI精准医学跨组学（TOPMed）计划将通过收集和耦合全基因组测序（WGS）和其他组学数据（例如，DNA甲基化特征、RNA表达谱、代谢物谱）与来自心脏、肺、血液和睡眠（HLBS）疾病研究的分子、行为、成像、环境和临床数据。 TOPMed计划旨在： ·使用WGS收集和组装组学（RNASeq，甲基化，代谢组学，表观基因组学和蛋白质组学）数据以及不同人群（包括传统上在研究中代表性不足的人群）的临床结果数据。 ·建立一个数据共享库，科学界可以用于未来的研究，并实现精准医学。 ·刺激系统医学方法，帮助组织数据，以确保它们可用于健康疾病研究。 ·促进发现HLBS疾病的基本机制。